The present application relates to machine learning, and more specifically, to labeling conversational data, for the purposes of machine learning.
For machines to have a natural language conversation with a human user, text analytic techniques, and conversational systems, the machine has to detect social actions the user is performing in order to determine user intent and to respond appropriately. Current solutions typically label utterances in conversational data in terms of their “dialogue acts” and use these labels to train statistical classifiers. Alternatively, some solutions (such as Dialog Act Markup in Several Layers (DAMSL)) label utterances in terms of whether they are repairs on previous or “antecedent” turns.